Day 0 Support: Claude Sonnet 5

LiteLLM now supports Claude Sonnet 5 on Day 0. Use it across Anthropic, Azure, Vertex AI, and Bedrock through the LiteLLM AI Gateway. Call it with the same OpenAI-compatible request you already use, and track spend, rate limits, and logging in one place.

What's new in Sonnet 5

Sonnet 5 is the most agentic Sonnet model yet, with performance close to Opus 4.8 at a fraction of the price. A few things stand out for teams running it through a gateway:

• Opus-class quality, Sonnet pricing. Anthropic reports Sonnet 5 performs close to Opus 4.8 while costing far less, and is a substantial step up from Sonnet 4.6 on reasoning, tool use, coding, and knowledge work. (details from Anthropic)
• Built to run agents. It plans, drives tools like browsers and terminals, runs autonomously, and checks its own output without being asked, finishing complex tasks where earlier Sonnet models would stop short. Anthropic highlights gains on BrowseComp (agentic search) and OSWorld-Verified (computer use).
• Adaptive thinking only. Sonnet 5 decides how deeply to think on its own. You steer it per request with reasoning_effort or output_config.effort; fixed thinking budgets, temperature, top_p, and assistant message prefill are not supported by the model.
• $3 / MTok input and $15 / MTok output, with prompt caching at $0.30 / MTok (read) and $3.75 / MTok (write). Anthropic is running introductory pricing of $2 / MTok input and $10 / MTok output through August 31, 2026. On Bedrock, the us., eu., au., and jp. inference profiles carry the usual 10% regional premium while global. stays at base price; LiteLLM tracks every variant automatically.
• 1M-token context, up to 128K output tokens.
• One gateway, every surface. Vision, PDF input, computer use, tool calling, prompt caching, adaptive thinking, and structured output, all available across Anthropic, Azure, Vertex AI, and Bedrock with unified spend tracking, logging, and fallbacks.

Enabling Sonnet 5

Sonnet 5 ships in the v1.92.0-dev.1 image (and every release after it). How you pick it up depends on where your proxy reads pricing from:

• Default (remote cost map): no upgrade needed. In the LiteLLM UI, open the Price Data tab under Models + Endpoints and click Reload Price Data (or, as a proxy admin, POST /reload/model_cost_map). This refetches the latest pricing from LiteLLM's cost map and re-registers provider routing in one step, so claude-sonnet-5 becomes available across Anthropic, Azure, Vertex AI, and Bedrock, even if you're on an older proxy version.

• Running LITELLM_LOCAL_MODEL_COST_MAP=true? The cost map is baked into the image, so the Reload button won't reach it. Pull v1.92.0-dev.1 or later to get the bundled Sonnet 5 metadata:

  docker pull ghcr.io/berriai/litellm:v1.92.0-dev.1

Usage

Pick your provider below. Each tab wires up claude-sonnet-5 for that provider; the request you send afterward is identical everywhere.

Anthropic

1. Setup config.yaml

model_list:
  - model_name: claude-sonnet-5
    litellm_params:
      model: anthropic/claude-sonnet-5
      api_key: os.environ/ANTHROPIC_API_KEY

2. Start the proxy

docker run -d \
  -p 4000:4000 \
  -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY \
  -v $(pwd)/config.yaml:/app/config.yaml \
  ghcr.io/berriai/litellm:v1.92.0-dev.1 \
  --config /app/config.yaml

Azure

1. Setup config.yaml

model_list:
  - model_name: claude-sonnet-5
    litellm_params:
      model: azure_ai/claude-sonnet-5
      api_key: os.environ/AZURE_AI_API_KEY
      api_base: os.environ/AZURE_AI_API_BASE  # https://<resource>.services.ai.azure.com

2. Start the proxy

docker run -d \
  -p 4000:4000 \
  -e AZURE_AI_API_KEY=$AZURE_AI_API_KEY \
  -e AZURE_AI_API_BASE=$AZURE_AI_API_BASE \
  -v $(pwd)/config.yaml:/app/config.yaml \
  ghcr.io/berriai/litellm:v1.92.0-dev.1 \
  --config /app/config.yaml

Vertex AI

1. Setup config.yaml

model_list:
  - model_name: claude-sonnet-5
    litellm_params:
      model: vertex_ai/claude-sonnet-5
      vertex_project: os.environ/VERTEX_PROJECT
      vertex_location: global

2. Start the proxy

docker run -d \
  -p 4000:4000 \
  -e VERTEX_PROJECT=$VERTEX_PROJECT \
  -e GOOGLE_APPLICATION_CREDENTIALS=/app/credentials.json \
  -v $(pwd)/config.yaml:/app/config.yaml \
  -v $(pwd)/credentials.json:/app/credentials.json \
  ghcr.io/berriai/litellm:v1.92.0-dev.1 \
  --config /app/config.yaml

Bedrock

1. Setup config.yaml

model_list:
  - model_name: claude-sonnet-5
    litellm_params:
      model: bedrock/anthropic.claude-sonnet-5
      aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID
      aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY
      aws_region_name: us-east-1

note

For cross-region routing, swap the model ID for a regional inference profile (us., eu., au., or jp. prefix), e.g. bedrock/converse/us.anthropic.claude-sonnet-5. These carry a 10% regional premium; the global. profile stays at base price. LiteLLM tracks the cost of each variant automatically.

2. Start the proxy

docker run -d \
  -p 4000:4000 \
  -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
  -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
  -v $(pwd)/config.yaml:/app/config.yaml \
  ghcr.io/berriai/litellm:v1.92.0-dev.1 \
  --config /app/config.yaml

3. Test it!

The request is the same regardless of which provider you configured above:

curl --location 'http://0.0.0.0:4000/chat/completions' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer $LITELLM_KEY' \
--data '{
  "model": "claude-sonnet-5",
  "messages": [
    {
      "role": "user",
      "content": "what llm are you"
    }
  ]
}'